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Construction of an experimental platform for electromagnetic hydraulic fracturing fracture monitoring under the background of integration of production and education

Kai ZHANG, Liming ZHANG, Peiyin JIANG, Lihong YUE, Xingyu ZHOU, Qinyang DAI, Jingqi LIN

Experimental Technology and Management 2024, 41(5): 151-160

Published: 20 May 2024

Abstract

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[Objective]

Hydraulic fracturing technology is pivotal in the exploration and development of oil and gas fields. Among various methods, electromagnetic monitoring stands out for its nondestructive nature and high accuracy, proving to be an effective tool for evaluating hydraulic fracturing. This paper aims to advance the field by enhancing traditional fracture monitoring devices and creating an experimental teaching platform for online monitoring of hydraulic fractures using electromagnetic methods.

[Methods]

The proposed teaching platform integrates both numerical simulations and laboratory experiments. Initially, COMSOL software was used to conduct numerical simulations on the electromagnetic crack monitoring process, and then the laboratory experiment scheme was optimized based on the numerical simulation results. Subsequently, the teacher guided the students to conduct the laboratory fracture model monitoring experiment, and compared their results with those from the numerical simulations. This dual approach, combining virtual simulation experiments with hands-on laboratory work, allows for a deep dive into electromagnetic fracture monitoring technology. It opens avenues to explore the relationship between electromagnetic monitoring signals and fracture parameters more thoroughly. In the simulation phase, COMSOL was used to model the three-dimensional formation, wellbore, fracture, and electromagnetic detection tool. The mathematical model and boundary conditions of finite-element simulations were established based on Maxwell’s equations, and each model is meshed according to its interconnectivity. After establishing the simulation model, experiments were carried out to monitor the electromagnetic response signals of different fracture models. Numerical simulation exercises not only address students’ uncertainties and complexities in the subject matter but also enhance their understanding and feedback on the experiment. The laboratory experiments, designed to mirror field fracturing processes, feature a visual fracture simulation system and a three-dimensional electromagnetic induction probe. Through this setup, students directly observe the fracture filling and monitoring process, collecting electromagnetic response signals with the probe. Laboratory experiments can exercise students’ practical skills. Comparing these experimental results with numerical simulation results improves the comprehensive research ability of students.

[Results]

The comparative analysis of electromagnetic fracture monitoring results from both numeral simulations and laboratory experiments reveals 1) a positive correlation between the signal amplitude fluctuations and the total volume of fracture; 2) the ability to infer the fracture location based on the signal fluctuation range; and 3) the similarity between numerical simulation results and experimental data, affirming the accuracy of the experiment.

[Conclusions]

The teaching platform for electromagnetic monitoring of hydraulic fractures combines virtual simulation experiments with indoor electromagnetic signal monitoring to deepen the understanding of electromagnetic fracture monitoring technology. Through a series of educational modules, including COMSOL virtual fracture simulations, monitoring of fracture filling processes, laboratory fracture monitoring, and comparative analysis of monitoring signals, students explore the relationship between fracture parameters and electromagnetic monitoring signals. This comprehensive approach not only lays a theoretical foundation for the effective inversion of fracture parameters but also enhances student’s grasp of relevant theoretical concepts, fostering their research and engineering practice skills. By engaging with this cutting-edge academic and applied experimental project, students are encouraged to develop their independent innovation and practical inquiry abilities. The platform promotes the advancement of hydraulic fracture monitoring technology. In addition, the teaching platform has been upgraded by adopting constructive and innovative ideas, positioning itself at the forefront of innovative research in the field.

Open Access Original Paper Issue

Multi-surrogate framework with an adaptive selection mechanism for production optimization

Jia-Lin Wang, Li-Ming Zhang, Kai Zhang, Jian Wang, Jian-Ping Zhou, Wen-Feng Peng, Fa-Liang Yin, Chao Zhong, Xia Yan, Pi-Yang Liu, Hua-Qing Zhang, Yong-Fei Yang, Hai Sun

Petroleum Science 2024, 21(1): 366-383

Published: 26 August 2023

Abstract

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Data-driven surrogate models that assist with efficient evolutionary algorithms to find the optimal development scheme have been widely used to solve reservoir production optimization problems. However, existing research suggests that the effectiveness of a surrogate model can vary depending on the complexity of the design problem. A surrogate model that has demonstrated success in one scenario may not perform as well in others. In the absence of prior knowledge, finding a promising surrogate model that performs well for an unknown reservoir is challenging. Moreover, the optimization process often relies on a single evolutionary algorithm, which can yield varying results across different cases. To address these limitations, this paper introduces a novel approach called the multi-surrogate framework with an adaptive selection mechanism (MSFASM) to tackle production optimization problems. MSFASM consists of two stages. In the first stage, a reduced-dimensional broad learning system (BLS) is used to adaptively select the evolutionary algorithm with the best performance during the current optimization period. In the second stage, the multi-objective algorithm, non-dominated sorting genetic algorithm II (NSGA-II), is used as an optimizer to find a set of Pareto solutions with good performance on multiple surrogate models. A novel optimal point criterion is utilized in this stage to select the Pareto solutions, thereby obtaining the desired development schemes without increasing the computational load of the numerical simulator. The two stages are combined using sequential transfer learning. From the two most important perspectives of an evolutionary algorithm and a surrogate model, the proposed method improves adaptability to optimization problems of various reservoir types. To verify the effectiveness of the proposed method, four 100-dimensional benchmark functions and two reservoir models are tested, and the results are compared with those obtained by six other surrogate-model-based methods. The results demonstrate that our approach can obtain the maximum net present value (NPV) of the target production optimization problems.

Open Access Original Article Issue

The application of improved differential evolution algorithm in electromagnetic fracture monitoring

Ji Qi, Liming Zhang, Kai Zhang, Lixin Li, Jijia Sun

Advances in Geo-Energy Research 2020, 4(3): 233-246

Published: 07 June 2020

Abstract

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Hydraulic fracturing is a pivotal technology in the development of unconventional tight reservoirs, in which accurate monitoring of fracture parameters is significant. This paper proposes an improved differential evolution algorithm (EMDE) to calculate the Effective Propped Volume (EPV) accurately. The forward simulation results demonstrate that when the transmitting source plane is in a particular position, the relationship between signals and a specific parameter is the most obvious, providing a basis for the application of inversion algorithms. Furthermore, the difference between the population center and the individual is added to accelerate the convergence of the EMDE algorithm. A simplified selection strategy of the simulated annealing algorithm is used to enhance the convergence speed and the ability to find the global optimal value of the objective function simultaneously. The one-stage and two-stages inversion strategies are designed to calculate the parameters. In the two-stage inversion, the second-stage is constrained by the forward simulation and the first-stage results. It indicates that the errors of the two-stages inversion can be controlled within 5%. Through the inversion simulation proposed in this paper, the feasibility of the electromagnetic method to monitor the EPV is verified, and it provides a theoretical guidance for subsequent fracturing construction adjustments.